Overview

Dataset statistics

Number of variables11
Number of observations1000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory126.0 KiB
Average record size in memory129.1 B

Variable types

Text5
Numeric6

Alerts

Metascore is highly overall correlated with RatingHigh correlation
Rating is highly overall correlated with Metascore and 1 other fieldsHigh correlation
Votes is highly overall correlated with Rating and 1 other fieldsHigh correlation
Year is highly overall correlated with VotesHigh correlation
Description has unique valuesUnique

Reproduction

Analysis started2024-02-05 13:50:20.050527
Analysis finished2024-02-05 13:50:23.267012
Duration3.22 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Title
Text

Distinct999
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:23.384333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length44
Mean length14.539
Min length2

Characters and Unicode

Total characters14539
Distinct characters81
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique998 ?
Unique (%)99.8%

Sample

1st rowGuardians of the Galaxy
2nd rowPrometheus
3rd rowSplit
4th rowSing
5th rowSuicide Squad
ValueCountFrequency (%)
the 305
 
11.7%
of 92
 
3.5%
a 29
 
1.1%
in 22
 
0.8%
and 22
 
0.8%
2 22
 
0.8%
15
 
0.6%
man 12
 
0.5%
to 12
 
0.5%
i 11
 
0.4%
Other values (1429) 2063
79.2%
2024-02-05T15:50:23.636297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1605
 
11.0%
e 1507
 
10.4%
a 884
 
6.1%
o 851
 
5.9%
n 828
 
5.7%
r 799
 
5.5%
i 775
 
5.3%
t 720
 
5.0%
s 609
 
4.2%
h 539
 
3.7%
Other values (71) 5422
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10340
71.1%
Uppercase Letter 2274
 
15.6%
Space Separator 1605
 
11.0%
Other Punctuation 171
 
1.2%
Decimal Number 110
 
0.8%
Dash Punctuation 31
 
0.2%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1507
14.6%
a 884
 
8.5%
o 851
 
8.2%
n 828
 
8.0%
r 799
 
7.7%
i 775
 
7.5%
t 720
 
7.0%
s 609
 
5.9%
h 539
 
5.2%
l 457
 
4.4%
Other values (22) 2371
22.9%
Uppercase Letter
ValueCountFrequency (%)
T 350
15.4%
S 188
 
8.3%
M 141
 
6.2%
B 133
 
5.8%
D 125
 
5.5%
A 115
 
5.1%
P 110
 
4.8%
H 105
 
4.6%
C 104
 
4.6%
W 100
 
4.4%
Other values (16) 803
35.3%
Decimal Number
ValueCountFrequency (%)
2 35
31.8%
3 17
15.5%
0 15
13.6%
1 15
13.6%
5 7
 
6.4%
4 7
 
6.4%
7 5
 
4.5%
6 3
 
2.7%
8 3
 
2.7%
9 3
 
2.7%
Other Punctuation
ValueCountFrequency (%)
: 85
49.7%
' 39
22.8%
. 23
 
13.5%
, 9
 
5.3%
& 6
 
3.5%
! 4
 
2.3%
/ 2
 
1.2%
? 2
 
1.2%
· 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12614
86.8%
Common 1925
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1507
 
11.9%
a 884
 
7.0%
o 851
 
6.7%
n 828
 
6.6%
r 799
 
6.3%
i 775
 
6.1%
t 720
 
5.7%
s 609
 
4.8%
h 539
 
4.3%
l 457
 
3.6%
Other values (48) 4645
36.8%
Common
ValueCountFrequency (%)
1605
83.4%
: 85
 
4.4%
' 39
 
2.0%
2 35
 
1.8%
- 31
 
1.6%
. 23
 
1.2%
3 17
 
0.9%
0 15
 
0.8%
1 15
 
0.8%
, 9
 
0.5%
Other values (13) 51
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14530
99.9%
None 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1605
 
11.0%
e 1507
 
10.4%
a 884
 
6.1%
o 851
 
5.9%
n 828
 
5.7%
r 799
 
5.5%
i 775
 
5.3%
t 720
 
5.0%
s 609
 
4.2%
h 539
 
3.7%
Other values (64) 5413
37.3%
None
ValueCountFrequency (%)
é 3
33.3%
ä 1
 
11.1%
í 1
 
11.1%
á 1
 
11.1%
ç 1
 
11.1%
· 1
 
11.1%
è 1
 
11.1%

Genre
Text

Distinct207
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:23.766480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length18.095
Min length5

Characters and Unicode

Total characters18095
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)8.5%

Sample

1st rowAction,Adventure,Sci-Fi
2nd rowAdventure,Mystery,Sci-Fi
3rd rowHorror,Thriller
4th rowAnimation,Comedy,Family
5th rowAction,Adventure,Fantasy
ValueCountFrequency (%)
action,adventure,sci-fi 50
 
5.0%
drama 48
 
4.8%
comedy,drama,romance 35
 
3.5%
comedy 32
 
3.2%
drama,romance 31
 
3.1%
animation,adventure,comedy 27
 
2.7%
action,adventure,fantasy 27
 
2.7%
comedy,drama 27
 
2.7%
comedy,romance 26
 
2.6%
crime,drama,thriller 24
 
2.4%
Other values (197) 673
67.3%
2024-02-05T15:50:23.972455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1923
 
10.6%
a 1568
 
8.7%
, 1555
 
8.6%
e 1403
 
7.8%
m 1183
 
6.5%
i 1168
 
6.5%
o 1138
 
6.3%
n 909
 
5.0%
t 872
 
4.8%
y 753
 
4.2%
Other values (21) 5623
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13745
76.0%
Uppercase Letter 2675
 
14.8%
Other Punctuation 1555
 
8.6%
Dash Punctuation 120
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 1923
14.0%
a 1568
11.4%
e 1403
10.2%
m 1183
8.6%
i 1168
8.5%
o 1138
8.3%
n 909
6.6%
t 872
 
6.3%
y 753
 
5.5%
c 585
 
4.3%
Other values (8) 2243
16.3%
Uppercase Letter
ValueCountFrequency (%)
A 611
22.8%
D 513
19.2%
C 429
16.0%
F 272
10.2%
T 195
 
7.3%
H 148
 
5.5%
R 141
 
5.3%
S 138
 
5.2%
M 127
 
4.7%
B 81
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 1555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16420
90.7%
Common 1675
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 1923
 
11.7%
a 1568
 
9.5%
e 1403
 
8.5%
m 1183
 
7.2%
i 1168
 
7.1%
o 1138
 
6.9%
n 909
 
5.5%
t 872
 
5.3%
y 753
 
4.6%
A 611
 
3.7%
Other values (19) 4892
29.8%
Common
ValueCountFrequency (%)
, 1555
92.8%
- 120
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 1923
 
10.6%
a 1568
 
8.7%
, 1555
 
8.6%
e 1403
 
7.8%
m 1183
 
6.5%
i 1168
 
6.5%
o 1138
 
6.3%
n 909
 
5.0%
t 872
 
4.8%
y 753
 
4.2%
Other values (21) 5623
31.1%

Description
Text

UNIQUE 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:24.117465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length421
Median length212
Mean length163.232
Min length42

Characters and Unicode

Total characters163232
Distinct characters82
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowA group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.
2nd rowFollowing clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.
3rd rowThree girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.
4th rowIn a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.
5th rowA secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.
ValueCountFrequency (%)
a 1626
 
5.8%
the 1360
 
4.9%
to 934
 
3.3%
of 807
 
2.9%
and 716
 
2.6%
in 578
 
2.1%
his 487
 
1.7%
an 304
 
1.1%
is 296
 
1.1%
with 274
 
1.0%
Other values (6172) 20539
73.6%
2024-02-05T15:50:24.473325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26921
16.5%
e 15840
 
9.7%
t 10926
 
6.7%
a 10686
 
6.5%
i 9657
 
5.9%
o 9618
 
5.9%
n 9602
 
5.9%
r 9227
 
5.7%
s 8727
 
5.3%
h 6513
 
4.0%
Other values (72) 45515
27.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 128516
78.7%
Space Separator 26921
 
16.5%
Uppercase Letter 3786
 
2.3%
Other Punctuation 2995
 
1.8%
Decimal Number 506
 
0.3%
Dash Punctuation 438
 
0.3%
Close Punctuation 24
 
< 0.1%
Open Punctuation 24
 
< 0.1%
Final Punctuation 20
 
< 0.1%
Currency Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15840
12.3%
t 10926
 
8.5%
a 10686
 
8.3%
i 9657
 
7.5%
o 9618
 
7.5%
n 9602
 
7.5%
r 9227
 
7.2%
s 8727
 
6.8%
h 6513
 
5.1%
l 5169
 
4.0%
Other values (20) 32551
25.3%
Uppercase Letter
ValueCountFrequency (%)
A 688
18.2%
T 290
 
7.7%
S 271
 
7.2%
B 227
 
6.0%
W 211
 
5.6%
C 204
 
5.4%
I 201
 
5.3%
M 192
 
5.1%
F 142
 
3.8%
H 140
 
3.7%
Other values (16) 1220
32.2%
Other Punctuation
ValueCountFrequency (%)
. 1365
45.6%
, 1216
40.6%
' 297
 
9.9%
" 66
 
2.2%
: 26
 
0.9%
? 11
 
0.4%
; 8
 
0.3%
/ 4
 
0.1%
! 1
 
< 0.1%
# 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 110
21.7%
0 108
21.3%
9 92
18.2%
2 53
10.5%
7 31
 
6.1%
8 28
 
5.5%
6 25
 
4.9%
5 23
 
4.5%
4 23
 
4.5%
3 13
 
2.6%
Space Separator
ValueCountFrequency (%)
26921
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Final Punctuation
ValueCountFrequency (%)
» 20
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 132302
81.1%
Common 30930
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15840
12.0%
t 10926
 
8.3%
a 10686
 
8.1%
i 9657
 
7.3%
o 9618
 
7.3%
n 9602
 
7.3%
r 9227
 
7.0%
s 8727
 
6.6%
h 6513
 
4.9%
l 5169
 
3.9%
Other values (46) 36337
27.5%
Common
ValueCountFrequency (%)
26921
87.0%
. 1365
 
4.4%
, 1216
 
3.9%
- 438
 
1.4%
' 297
 
1.0%
1 110
 
0.4%
0 108
 
0.3%
9 92
 
0.3%
" 66
 
0.2%
2 53
 
0.2%
Other values (16) 264
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163203
> 99.9%
None 29
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26921
16.5%
e 15840
 
9.7%
t 10926
 
6.7%
a 10686
 
6.5%
i 9657
 
5.9%
o 9618
 
5.9%
n 9602
 
5.9%
r 9227
 
5.7%
s 8727
 
5.3%
h 6513
 
4.0%
Other values (67) 45486
27.9%
None
ValueCountFrequency (%)
» 20
69.0%
é 4
 
13.8%
á 2
 
6.9%
è 2
 
6.9%
í 1
 
3.4%

Director
Text

Distinct644
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:24.627177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length13.139
Min length3

Characters and Unicode

Total characters13139
Distinct characters69
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique444 ?
Unique (%)44.4%

Sample

1st rowJames Gunn
2nd rowRidley Scott
3rd rowM. Night Shyamalan
4th rowChristophe Lourdelet
5th rowDavid Ayer
ValueCountFrequency (%)
david 38
 
1.8%
john 25
 
1.2%
michael 22
 
1.1%
james 21
 
1.0%
scott 20
 
1.0%
paul 19
 
0.9%
robert 14
 
0.7%
steven 13
 
0.6%
lee 12
 
0.6%
peter 12
 
0.6%
Other values (977) 1896
90.6%
2024-02-05T15:50:24.866388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1223
 
9.3%
1092
 
8.3%
a 1056
 
8.0%
n 937
 
7.1%
r 875
 
6.7%
o 783
 
6.0%
i 740
 
5.6%
l 604
 
4.6%
t 486
 
3.7%
s 467
 
3.6%
Other values (59) 4876
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9802
74.6%
Uppercase Letter 2153
 
16.4%
Space Separator 1092
 
8.3%
Other Punctuation 73
 
0.6%
Dash Punctuation 19
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1223
12.5%
a 1056
10.8%
n 937
9.6%
r 875
 
8.9%
o 783
 
8.0%
i 740
 
7.5%
l 604
 
6.2%
t 486
 
5.0%
s 467
 
4.8%
h 357
 
3.6%
Other values (28) 2274
23.2%
Uppercase Letter
ValueCountFrequency (%)
S 207
 
9.6%
J 200
 
9.3%
M 183
 
8.5%
A 148
 
6.9%
D 137
 
6.4%
G 131
 
6.1%
B 127
 
5.9%
C 123
 
5.7%
R 119
 
5.5%
L 108
 
5.0%
Other values (17) 670
31.1%
Other Punctuation
ValueCountFrequency (%)
. 71
97.3%
' 2
 
2.7%
Space Separator
ValueCountFrequency (%)
1092
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11955
91.0%
Common 1184
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1223
 
10.2%
a 1056
 
8.8%
n 937
 
7.8%
r 875
 
7.3%
o 783
 
6.5%
i 740
 
6.2%
l 604
 
5.1%
t 486
 
4.1%
s 467
 
3.9%
h 357
 
3.0%
Other values (55) 4427
37.0%
Common
ValueCountFrequency (%)
1092
92.2%
. 71
 
6.0%
- 19
 
1.6%
' 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13095
99.7%
None 44
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1223
 
9.3%
1092
 
8.3%
a 1056
 
8.1%
n 937
 
7.2%
r 875
 
6.7%
o 783
 
6.0%
i 740
 
5.7%
l 604
 
4.6%
t 486
 
3.7%
s 467
 
3.6%
Other values (46) 4832
36.9%
None
ValueCountFrequency (%)
é 11
25.0%
á 9
20.5%
ó 4
 
9.1%
ö 4
 
9.1%
å 4
 
9.1%
ç 3
 
6.8%
ñ 3
 
6.8%
ø 1
 
2.3%
ë 1
 
2.3%
û 1
 
2.3%
Other values (3) 3
 
6.8%

Actors
Text

Distinct996
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:24.993269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length70
Mean length58.288
Min length43

Characters and Unicode

Total characters58288
Distinct characters79
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique992 ?
Unique (%)99.2%

Sample

1st rowChris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana
2nd rowNoomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron
3rd rowJames McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula
4th rowMatthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson
5th rowWill Smith, Jared Leto, Margot Robbie, Viola Davis
ValueCountFrequency (%)
michael 62
 
0.8%
james 50
 
0.6%
tom 44
 
0.6%
john 42
 
0.5%
chris 42
 
0.5%
jason 41
 
0.5%
robert 37
 
0.5%
jennifer 35
 
0.4%
mark 35
 
0.4%
ben 31
 
0.4%
Other values (2924) 7441
94.7%
2024-02-05T15:50:25.223108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6860
 
11.8%
e 5007
 
8.6%
a 4812
 
8.3%
n 3867
 
6.6%
i 3216
 
5.5%
r 3171
 
5.4%
, 2999
 
5.1%
o 2949
 
5.1%
l 2811
 
4.8%
s 1931
 
3.3%
Other values (69) 20665
35.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39800
68.3%
Uppercase Letter 8428
 
14.5%
Space Separator 6860
 
11.8%
Other Punctuation 3117
 
5.3%
Dash Punctuation 81
 
0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5007
12.6%
a 4812
12.1%
n 3867
9.7%
i 3216
 
8.1%
r 3171
 
8.0%
o 2949
 
7.4%
l 2811
 
7.1%
s 1931
 
4.9%
t 1924
 
4.8%
h 1557
 
3.9%
Other values (33) 8555
21.5%
Uppercase Letter
ValueCountFrequency (%)
J 749
 
8.9%
M 725
 
8.6%
C 661
 
7.8%
S 632
 
7.5%
B 618
 
7.3%
A 520
 
6.2%
R 507
 
6.0%
D 473
 
5.6%
L 389
 
4.6%
H 385
 
4.6%
Other values (19) 2769
32.9%
Other Punctuation
ValueCountFrequency (%)
, 2999
96.2%
. 91
 
2.9%
' 27
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
6860
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 48228
82.7%
Common 10060
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5007
 
10.4%
a 4812
 
10.0%
n 3867
 
8.0%
i 3216
 
6.7%
r 3171
 
6.6%
o 2949
 
6.1%
l 2811
 
5.8%
s 1931
 
4.0%
t 1924
 
4.0%
h 1557
 
3.2%
Other values (62) 16983
35.2%
Common
ValueCountFrequency (%)
6860
68.2%
, 2999
29.8%
. 91
 
0.9%
- 81
 
0.8%
' 27
 
0.3%
0 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58177
99.8%
None 111
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6860
 
11.8%
e 5007
 
8.6%
a 4812
 
8.3%
n 3867
 
6.6%
i 3216
 
5.5%
r 3171
 
5.5%
, 2999
 
5.2%
o 2949
 
5.1%
l 2811
 
4.8%
s 1931
 
3.3%
Other values (49) 20554
35.3%
None
ValueCountFrequency (%)
é 29
26.1%
ë 16
14.4%
á 12
10.8%
í 10
 
9.0%
å 10
 
9.0%
ü 6
 
5.4%
ñ 5
 
4.5%
è 4
 
3.6%
Ó 3
 
2.7%
ó 2
 
1.8%
Other values (10) 14
12.6%

Year
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.783
Minimum2006
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:25.301600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2007
Q12010
median2014
Q32016
95-th percentile2016
Maximum2016
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2059615
Coefficient of variation (CV)0.0015928004
Kurtosis-0.82196398
Mean2012.783
Median Absolute Deviation (MAD)2
Skewness-0.68987871
Sum2012783
Variance10.278189
MonotonicityNot monotonic
2024-02-05T15:50:25.374693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2016 297
29.7%
2015 127
12.7%
2014 98
 
9.8%
2013 91
 
9.1%
2012 64
 
6.4%
2011 63
 
6.3%
2010 60
 
6.0%
2007 53
 
5.3%
2008 52
 
5.2%
2009 51
 
5.1%
ValueCountFrequency (%)
2006 44
 
4.4%
2007 53
5.3%
2008 52
5.2%
2009 51
5.1%
2010 60
6.0%
2011 63
6.3%
2012 64
6.4%
2013 91
9.1%
2014 98
9.8%
2015 127
12.7%
ValueCountFrequency (%)
2016 297
29.7%
2015 127
12.7%
2014 98
 
9.8%
2013 91
 
9.1%
2012 64
 
6.4%
2011 63
 
6.3%
2010 60
 
6.0%
2009 51
 
5.1%
2008 52
 
5.2%
2007 53
 
5.3%

Runtime (Minutes)
Real number (ℝ)

Distinct94
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.172
Minimum66
Maximum191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:25.460235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile88
Q1100
median111
Q3123
95-th percentile150
Maximum191
Range125
Interquartile range (IQR)23

Descriptive statistics

Standard deviation18.810908
Coefficient of variation (CV)0.16621521
Kurtosis0.8583211
Mean113.172
Median Absolute Deviation (MAD)12
Skewness0.84671273
Sum113172
Variance353.85027
MonotonicityNot monotonic
2024-02-05T15:50:25.549450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108 31
 
3.1%
100 28
 
2.8%
117 27
 
2.7%
118 26
 
2.6%
106 26
 
2.6%
110 26
 
2.6%
102 25
 
2.5%
112 24
 
2.4%
123 23
 
2.3%
104 23
 
2.3%
Other values (84) 741
74.1%
ValueCountFrequency (%)
66 1
 
0.1%
73 2
 
0.2%
80 2
 
0.2%
81 5
0.5%
82 1
 
0.1%
83 6
0.6%
84 3
 
0.3%
85 9
0.9%
86 8
0.8%
87 9
0.9%
ValueCountFrequency (%)
191 1
 
0.1%
187 1
 
0.1%
180 3
0.3%
172 1
 
0.1%
170 1
 
0.1%
169 3
0.3%
166 1
 
0.1%
165 5
0.5%
164 1
 
0.1%
163 1
 
0.1%

Rating
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7232
Minimum1.9
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:25.628843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile5.1
Q16.2
median6.8
Q37.4
95-th percentile8.1
Maximum9
Range7.1
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.94542879
Coefficient of variation (CV)0.14062185
Kurtosis1.3222703
Mean6.7232
Median Absolute Deviation (MAD)0.6
Skewness-0.74314194
Sum6723.2
Variance0.8938356
MonotonicityNot monotonic
2024-02-05T15:50:25.728294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.1 52
 
5.2%
6.7 48
 
4.8%
7 46
 
4.6%
6.3 44
 
4.4%
7.3 42
 
4.2%
7.2 42
 
4.2%
6.6 42
 
4.2%
6.5 40
 
4.0%
7.8 40
 
4.0%
6.2 37
 
3.7%
Other values (45) 567
56.7%
ValueCountFrequency (%)
1.9 1
 
0.1%
2.7 2
0.2%
3.2 1
 
0.1%
3.5 2
0.2%
3.7 2
0.2%
3.9 3
0.3%
4 1
 
0.1%
4.1 1
 
0.1%
4.2 2
0.2%
4.3 4
0.4%
ValueCountFrequency (%)
9 1
 
0.1%
8.8 2
 
0.2%
8.6 3
 
0.3%
8.5 6
 
0.6%
8.4 4
 
0.4%
8.3 7
 
0.7%
8.2 10
 
1.0%
8.1 26
2.6%
8 19
1.9%
7.9 23
2.3%

Votes
Real number (ℝ)

HIGH CORRELATION 

Distinct997
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169808.26
Minimum61
Maximum1791916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:25.819991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile1260.35
Q136309
median110799
Q3239909.75
95-th percentile526551.85
Maximum1791916
Range1791855
Interquartile range (IQR)203600.75

Descriptive statistics

Standard deviation188762.65
Coefficient of variation (CV)1.1116223
Kurtosis11.312681
Mean169808.26
Median Absolute Deviation (MAD)88402
Skewness2.5079185
Sum1.6980826 × 108
Variance3.5631337 × 1010
MonotonicityNot monotonic
2024-02-05T15:50:25.916078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
97141 2
 
0.2%
291 2
 
0.2%
1427 2
 
0.2%
757074 1
 
0.1%
5796 1
 
0.1%
168875 1
 
0.1%
136323 1
 
0.1%
26320 1
 
0.1%
75291 1
 
0.1%
206707 1
 
0.1%
Other values (987) 987
98.7%
ValueCountFrequency (%)
61 1
0.1%
96 1
0.1%
102 1
0.1%
115 1
0.1%
164 1
0.1%
173 1
0.1%
178 1
0.1%
198 1
0.1%
202 1
0.1%
220 1
0.1%
ValueCountFrequency (%)
1791916 1
0.1%
1583625 1
0.1%
1222645 1
0.1%
1047747 1
0.1%
1045588 1
0.1%
1039115 1
0.1%
959065 1
0.1%
937414 1
0.1%
935408 1
0.1%
913152 1
0.1%

Revenue (Millions)
Real number (ℝ)

Distinct815
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.956376
Minimum0
Maximum936.63
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:26.007153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.319
Q117.4425
median60.375
Q399.1775
95-th percentile281.2995
Maximum936.63
Range936.63
Interquartile range (IQR)81.735

Descriptive statistics

Standard deviation96.412043
Coefficient of variation (CV)1.1622017
Kurtosis12.596452
Mean82.956376
Median Absolute Deviation (MAD)41.395
Skewness2.7756667
Sum82956.376
Variance9295.282
MonotonicityNot monotonic
2024-02-05T15:50:26.092366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.95637615 128
 
12.8%
0.03 7
 
0.7%
0.01 5
 
0.5%
0.02 4
 
0.4%
0.04 4
 
0.4%
0.05 4
 
0.4%
0.32 4
 
0.4%
0.54 3
 
0.3%
2.2 3
 
0.3%
1.29 3
 
0.3%
Other values (805) 835
83.5%
ValueCountFrequency (%)
0 1
 
0.1%
0.01 5
0.5%
0.02 4
0.4%
0.03 7
0.7%
0.04 4
0.4%
0.05 4
0.4%
0.06 2
 
0.2%
0.07 2
 
0.2%
0.08 1
 
0.1%
0.09 2
 
0.2%
ValueCountFrequency (%)
936.63 1
0.1%
760.51 1
0.1%
652.18 1
0.1%
623.28 1
0.1%
533.32 1
0.1%
532.17 1
0.1%
486.29 1
0.1%
458.99 1
0.1%
448.13 1
0.1%
424.65 1
0.1%

Metascore
Real number (ℝ)

HIGH CORRELATION 

Distinct85
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.985043
Minimum11
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size47.9 KiB
2024-02-05T15:50:26.180331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile31
Q147.75
median58.985043
Q371
95-th percentile85
Maximum100
Range89
Interquartile range (IQR)23.25

Descriptive statistics

Standard deviation16.634858
Coefficient of variation (CV)0.28201825
Kurtosis-0.44853519
Mean58.985043
Median Absolute Deviation (MAD)11.985043
Skewness-0.12803962
Sum58985.043
Variance276.71851
MonotonicityNot monotonic
2024-02-05T15:50:26.269723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58.98504274 64
 
6.4%
66 25
 
2.5%
68 25
 
2.5%
72 25
 
2.5%
64 24
 
2.4%
57 23
 
2.3%
65 22
 
2.2%
51 22
 
2.2%
76 21
 
2.1%
81 21
 
2.1%
Other values (75) 728
72.8%
ValueCountFrequency (%)
11 1
 
0.1%
15 1
 
0.1%
16 1
 
0.1%
18 4
0.4%
19 1
 
0.1%
20 1
 
0.1%
22 3
0.3%
23 6
0.6%
24 2
 
0.2%
25 2
 
0.2%
ValueCountFrequency (%)
100 1
 
0.1%
99 1
 
0.1%
98 1
 
0.1%
96 4
0.4%
95 3
0.3%
94 3
0.3%
93 3
0.3%
92 2
 
0.2%
91 1
 
0.1%
90 5
0.5%

Interactions

2024-02-05T15:50:22.647068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.328950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.732046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.372446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.792964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.234599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.717817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.398514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.808491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.439578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.866969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.308206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.771779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.470056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.885072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.510713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.930390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.377310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.867649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.528228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.946425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.575059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.014661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.449297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.954942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.613186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.033800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.660583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.087875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.509832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:23.023511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:20.675457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.306010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:21.728657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.167170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-05T15:50:22.586049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-02-05T15:50:26.327723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
MetascoreRatingRevenue (Millions)Runtime (Minutes)VotesYear
Metascore1.0000.6410.0510.1890.261-0.058
Rating0.6411.0000.1070.3830.520-0.228
Revenue (Millions)0.0510.1071.0000.1820.498-0.152
Runtime (Minutes)0.1890.3830.1821.0000.408-0.174
Votes0.2610.5200.4980.4081.000-0.610
Year-0.058-0.228-0.152-0.174-0.6101.000

Missing values

2024-02-05T15:50:23.115426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-05T15:50:23.223281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TitleGenreDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)Metascore
Rank
1Guardians of the GalaxyAction,Adventure,Sci-FiA group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.James GunnChris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana20141218.1757074333.13000076.0
2PrometheusAdventure,Mystery,Sci-FiFollowing clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.Ridley ScottNoomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron20121247.0485820126.46000065.0
3SplitHorror,ThrillerThree girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.M. Night ShyamalanJames McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula20161177.3157606138.12000062.0
4SingAnimation,Comedy,FamilyIn a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.Christophe LourdeletMatthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson20161087.260545270.32000059.0
5Suicide SquadAction,Adventure,FantasyA secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.David AyerWill Smith, Jared Leto, Margot Robbie, Viola Davis20161236.2393727325.02000040.0
6The Great WallAction,Adventure,FantasyEuropean mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.Yimou ZhangMatt Damon, Tian Jing, Willem Dafoe, Andy Lau20161036.15603645.13000042.0
7La La LandComedy,Drama,MusicA jazz pianist falls for an aspiring actress in Los Angeles.Damien ChazelleRyan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons20161288.3258682151.06000093.0
8MindhornComedyA has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.Sean FoleyEssie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh2016896.4249082.95637671.0
9The Lost City of ZAction,Adventure,BiographyA true-life drama, centering on British explorer Col. Percival Fawcett, who disappeared while searching for a mysterious city in the Amazon in the 1920s.James GrayCharlie Hunnam, Robert Pattinson, Sienna Miller, Tom Holland20161417.171888.01000078.0
10PassengersAdventure,Drama,RomanceA spacecraft traveling to a distant colony planet and transporting thousands of people has a malfunction in its sleep chambers. As a result, two passengers are awakened 90 years early.Morten TyldumJennifer Lawrence, Chris Pratt, Michael Sheen,Laurence Fishburne20161167.0192177100.01000041.0
TitleGenreDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)Metascore
Rank
991Underworld: Rise of the LycansAction,Adventure,FantasyAn origins story centered on the centuries-old feud between the race of aristocratic vampires and their onetime slaves, the Lycans.Patrick TatopoulosRhona Mitra, Michael Sheen, Bill Nighy, Steven Mackintosh2009926.612970845.80000044.000000
992Taare Zameen ParDrama,Family,MusicAn eight-year-old boy is thought to be a lazy trouble-maker, until the new art teacher has the patience and compassion to discover the real problem behind his struggles in school.Aamir KhanDarsheel Safary, Aamir Khan, Tanay Chheda, Sachet Engineer20071658.51026971.20000042.000000
993Take Me Home TonightComedy,Drama,RomanceFour years after graduation, an awkward high school genius uses his sister's boyfriend's Labor Day party as the perfect opportunity to make his move on his high school crush.Michael DowseTopher Grace, Anna Faris, Dan Fogler, Teresa Palmer2011976.3454196.92000058.985043
994Resident Evil: AfterlifeAction,Adventure,HorrorWhile still out to destroy the evil Umbrella Corporation, Alice joins a group of survivors living in a prison surrounded by the infected who also want to relocate to the mysterious but supposedly unharmed safe haven known only as Arcadia.Paul W.S. AndersonMilla Jovovich, Ali Larter, Wentworth Miller,Kim Coates2010975.914090060.13000037.000000
995Project XComedy3 high school seniors throw a birthday party to make a name for themselves. As the night progresses, things spiral out of control as word of the party spreads.Nima NourizadehThomas Mann, Oliver Cooper, Jonathan Daniel Brown, Dax Flame2012886.716408854.72000048.000000
996Secret in Their EyesCrime,Drama,MysteryA tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.Billy RayChiwetel Ejiofor, Nicole Kidman, Julia Roberts, Dean Norris20151116.22758582.95637645.000000
997Hostel: Part IIHorrorThree American college students studying abroad are lured to a Slovakian hostel, and discover the grim reality behind it.Eli RothLauren German, Heather Matarazzo, Bijou Phillips, Roger Bart2007945.57315217.54000046.000000
998Step Up 2: The StreetsDrama,Music,RomanceRomantic sparks occur between two dance students from different backgrounds at the Maryland School of the Arts.Jon M. ChuRobert Hoffman, Briana Evigan, Cassie Ventura, Adam G. Sevani2008986.27069958.01000050.000000
999Search PartyAdventure,ComedyA pair of friends embark on a mission to reunite their pal with the woman he was going to marry.Scot ArmstrongAdam Pally, T.J. Miller, Thomas Middleditch,Shannon Woodward2014935.6488182.95637622.000000
1000Nine LivesComedy,Family,FantasyA stuffy businessman finds himself trapped inside the body of his family's cat.Barry SonnenfeldKevin Spacey, Jennifer Garner, Robbie Amell,Cheryl Hines2016875.31243519.64000011.000000